Method and apparatus for verifying user using multiple biometric verifiers

ABSTRACT

A user verification apparatus may perform user verification using multiple biometric verifiers. The user verification apparatus may set a termination stage of one or more biometric verifiers. Multiple biometric verifiers may be used to generate outputs, for which separate termination stages are set to establish a particular combination of set termination stages associated with the multiple biometric verifiers, and the user verification apparatus may fuse outputs of the biometric verifiers based on the particular combination of set termination stages. The user verification apparatus may verify a user based on a result of the fusing, and an unlocking command signal may be generated based on the verifying. The unlocking command signal may be generated to selectively grant access, to the verified user, to one or more elements of a device. The device may be a vehicle.

CROSS-REFERENCE TO RELATED APPLICATIONS

This U.S. non-provisional patent application claims priority under 35U.S.C. §119 to Korean Patent Application No. 10-2016-0087478 filed onJul. 11, 2016, and Korean Patent Application No. 10-2016-0130758 filedon Oct. 10, 2016, in the Korean Intellectual Property Office, the entirecontents of which are incorporated herein by reference in theirentirety.

BACKGROUND 1. Field

At least one example embodiment relates to user verification methods andapparatuses using a plurality of biometric verifiers.

2. Description of the Related Art

Biometrics-based verification or authentication technology may be usedto perform user verification using a fingerprint, a face, an iris, bloodvessels, and the like. Such biological characteristics used for theverification differ from individual to individual, rarely change duringa lifetime, and have a low risk of being stolen or copied. In addition,individuals do not need to intentionally carry such characteristics atall times and thus, may not suffer an inconvenience using the biologicalcharacteristics. However, due to an environmental condition, forexample, a temperature, an intensity of illumination, and a degree ofhumidity, misrecognition or misidentification may occur in biometricverification. Thus, verification technology using various pieces ofbiometric information simultaneously may be desired.

SUMMARY

At least one example embodiment relates to a user verification method.

In at least one example embodiment, the user verification method mayinclude setting a termination stage of each biometric verifier of aplurality of biometric verifiers, such that each biometric verifier ofthe plurality of biometric verifiers is associated with a separatetermination stage of a particular combination of termination stages,respectively. The user verification method may include executing theplurality of biometric verifiers, based on the particular combination oftermination stages associated with the plurality of biometric verifiers,to generate a plurality of outputs. The user verification method mayinclude fusing the plurality of outputs based on the particularcombination of termination stages associated with the plurality ofbiometric verifiers to generate a result. The user verification methodmay include verifying a user based on the result and generating anunlocking command signal to enable at least partial user access to adevice, based on the verifying.

Each biometric verifier may be configured to be executed to output anindividual verification result through a set of stages of the biometricverifier, the set of stages including at least one stage.

The set termination stage of the biometric verifier may be a particularstage of the plurality of stages. Each biometric verifier may beconfigured to be executed to output an individual verification resultcorresponding to the set termination stage of the biometric verifier.

The setting may include setting a termination stage at least onebiometric verifier based on a particular criterion.

The criterion may include an application type associated with a receivedverification request, a security level associated with the receivedverification request, a sensing environment associated with the userverification apparatus, a determination of whether the at least onebiometric verifier is to be executed to perform main verification orauxiliary verification, and/or a selection by a user at a userinterface.

The setting may include setting, to be the termination stage of the atleast one biometric verifier, a particular stage of the plurality ofstages of the at least one biometric verifier at which a verificationrate (VR) and a false acceptance rate (FAR) associated with anindividual verification result of the given stage at least meet athreshold VR and a threshold FAR, respectively, based on the particularcriterion.

The biometric verifiers may be configured to be executed to performbiometric verification of different modalities.

Each biometric verifier of the plurality of biometric verifiers may beconfigured to be executed to perform biometric verification based onreceived biometric information, the received biometric informationincluding one of a face, a fingerprint, an iris, a vein, palm lines, ashape of an ear, and an electrocardiogram (ECG).

The fusing may include fusing the plurality of outputs based onexecuting a fusion model corresponding to the particular combination oftermination stages associated with the plurality of biometric verifiersamong a plurality of fusion models associated with separate, respectivecombinations of termination stages associated with the plurality ofbiometric verifiers.

The verifying may include verifying the user based on comparing theresult of the fusing and a threshold value corresponding to theplurality of termination stages of the plurality of biometric verifiers.

At least one biometric verifier of the plurality of biometric verifiersmay include a fingerprint verifier. The fingerprint verifier may beconfigured to be executed to output an individual verification resultbased on executing each stage of a plurality of stages of thefingerprint verifier. Executing a first stage of the plurality of stagesmay include outputting an overlapping area and a matching score betweena registered fingerprint image and an input fingerprint image. Executinga second stage of the plurality of stages may include outputtingmatching scores between the registered fingerprint image and blocksgenerated based on partitioning the input fingerprint image.

At least one biometric verifier of the plurality of biometric verifiersmay include a face verifier. The face verifier may be configured to beexecuted to output an individual verification result of each layer basedon comparing features to be output by multiple layers in a neuralnetwork, based on an input image and features of a stored registeredimage corresponding to the layers.

The setting may include selecting one biometric verifier of theplurality of biometric verifiers as a main verifier, selecting anotherbiometric verifier of the plurality of biometric verifiers as asub-verifier, selecting, from a plurality of separate combinations of atermination stage of the main verifier and a termination stage of thesub-verifier, a particular combination of the termination stage of themain verifier and the termination stage of the sub-verifier thatincreases a level of the termination stage of the main verifier.

The fusing may include fusing the plurality of outputs using a fusionmodel configured to output a final verification result to verify theuser based on an input vector of a dimension corresponding to an outputof the set termination stage.

A non-transitory computer-readable medium may store instructions that,when executed by a processor, cause the processor to perform the userverification method.

At least one example embodiment relates to a user verificationapparatus.

In at least one example embodiment, a user verification apparatusincludes a memory storing a program of instructions and a processor. Theprocessor may be configured to execute the program of instructions toset a termination stage of each biometric verifier of a plurality ofbiometric verifiers, such that each biometric verifier of the pluralityof biometric verifiers is associated with a separate termination stageof a particular combination of termination stages, respectively. Theprocessor may be configured to execute the program of instructions toexecute the plurality of biometric verifiers, based on the particularcombination of termination stages associated with the plurality ofbiometric verifiers, to generate a plurality of outputs. The processormay be configured to execute the program of instructions to execute afusion model to fuse the plurality of outputs based on the particularcombination of termination stages associated with the plurality ofbiometric verifiers to generate a verification result. The processor maybe configured to execute the program of instructions to generate anunlocking command signal to enable at least partial user access to adevice, based on the verification result.

The processor may be configured to execute each given biometric verifierto output an individual verification result through a plurality ofstages of the given biometric verifier.

Each set termination stage may be a particular stage of a plurality ofstages associated with a particular biometric verifier of the pluralityof biometric verifiers. The processor may be configured to execute theprogram of instructions to output an individual verification resultcorresponding to the set termination stage associated with the biometricverifier, of the plurality of stages associated with the biometricverifier.

The processor may be configured to set the termination stage of at leastone biometric verifier based on a particular criterion.

The criterion may include an application type associated with a receivedverification request, a security level associated with the receivedverification request, a sensing environment associated with the userverification apparatus, a determination of whether the at least onebiometric verifier is to be executed to perform main verification orauxiliary verification, and/or a selection by a user at a userinterface.

The processor may be configured to set, to be the termination stage ofthe at least one biometric verifier, a particular stage of the pluralityof stages of the at least one biometric identifier at which averification rate (VR) and a false acceptance rate (FAR) associated withan individual verification result of the given stage at least meet athreshold VR and a threshold FAR, respectively, based on the criterion.

The processor may be configured to execute separate biometric verifiersto perform biometric verification of different modalities.

The processor may be configured to execute each biometric verifier ofthe plurality of biometric verifiers to perform biometric verificationbased on received biometric information, the received biometricinformation including one of a face, a fingerprint, an iris, a vein,palm lines, a shape of an ear, and an electrocardiogram (ECG).

The processor may be configured to fuse the plurality of outputs of theplurality of biometric verifiers, respectively, using a fusion modelcorresponding to the particular combination of termination stagesassociated with the plurality of biometric verifiers, among a pluralityof fusion models associated with separate, respective combinations oftermination stages associated with the plurality of biometric verifiers.

At least one biometric verifier of the plurality of biometric verifiersmay include a fingerprint verifier. The processor may be configured toexecute the fingerprint verifier to output an individual verificationresult based on executing each stage of a plurality of stages of thefingerprint verifier. Executing a first stage of the plurality of stagesmay include outputting an overlapping area and a matching score betweena registered fingerprint image and an input fingerprint image. Executinga second stage of the plurality of stages may include outputtingmatching scores between the registered fingerprint image and blocksgenerated based on partitioning the input fingerprint image.

At least one biometric verifier of the plurality of biometric verifiersmay include a face verifier. The processor may be configured to executethe face verifier to output an individual verification result of eachlayer based on comparing features to be output by multiple layers in aneural network, based on an input image and features of a storedregistered image corresponding to the layers.

Executing the fusion model may include outputting a final verificationresult for user verification based on an input vector of a dimensioncorresponding to an output of the particular combination of terminationstages associated with the plurality of biometric verifiers.

The processor may be configured to select one biometric verifier of theplurality of biometric verifiers as a main verifier, select anotherbiometric verifier of the plurality of biometric verifiers as asub-verifier, set a minimum stage of the main verifier, from among aplurality of stages of the main verifier, to be a termination stage ofthe main verifier, and set a maximum stage of the sub-verifier, fromamong a plurality of stages of the sub-verifier, to be a terminationstage of the sub-verifier.

In at least one example embodiment, a user verification apparatus, mayinclude a memory storing a program of instructions and a processor. Theprocessor may be configured to execute the program of instructions toreceive a user verification request, the user verification requestincluding a criterion. The processor may be configured to execute theprogram of instructions to set a termination stage of a biometricverifier based on the criterion. The processor may be configured toexecute the program of instructions to execute the biometric verifier,based on the set termination stage, to generate an individualverification result. The processor may be configured to execute theprogram of instructions to verify a user based on the individualverification result. The processor may be configured to execute theprogram of instructions to generate an unlocking command signal toenable at least partial user access to a device, based on the verifying.

The user verification apparatus may include a vehicle configured totransport one or more occupants. The generating the unlocking commandsignal may include selectively granting, to the user, access to aninterior of the vehicle based on the verifying, and/or selectivelygrant, to the user, control over one or more driving elements of thevehicle based on the verifying.

Additional aspects of example embodiments will be set forth in part inthe description which follows and, in part, will be apparent from thedescription, or may be learned by practice of the disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features of inventive concepts will be apparentfrom the more particular description of non-limiting embodiments ofinventive concepts, as illustrated in the accompanying drawings in whichlike reference characters refer to like parts throughout the differentviews. The drawings are not necessarily to scale, emphasis instead beingplaced upon illustrating principles of inventive concepts. In thedrawings:

FIG. 1 is a diagram illustrating a user verification system according toat least one example embodiment;

FIG. 2 is a diagram illustrating a user verification apparatus accordingto at least one example embodiment;

FIG. 3 is a diagram illustrating a fusion model according to at leastone example embodiment;

FIGS. 4A and 4B are diagrams illustrating a verification rate (VR) and afalse acceptance rate (FAR) of a fusion model according to at least oneexample embodiment;

FIG. 5 is a diagram illustrating a fingerprint verifier according to atleast one example embodiment;

FIG. 6 is a diagram illustrating a process of matching based on a changein an input fingerprint image according to at least one exampleembodiment;

FIG. 7 is a diagram illustrating a process of partitioning an inputfingerprint image and of matching according to at least one exampleembodiment;

FIG. 8 is a diagram illustrating a face verifier according to at leastone example embodiment;

FIG. 9 is a diagram illustrating a plurality of layers included in aface verifier according to at least one example embodiment;

FIG. 10 is a diagram illustrating a main verifier and a sub-verifieraccording to at least one example embodiment;

FIG. 11 is a flowchart illustrating a user verification method accordingto at least one example embodiment; and

FIG. 12 is a diagram illustrating an electronic system according to atleast one example embodiment.

DETAILED DESCRIPTION

Hereinafter, at least one example embodiment will be described in detailwith reference to the accompanying drawings. Regarding the referencenumerals assigned to the elements in the drawings, it should be notedthat the same elements will be designated by the same referencenumerals, wherever possible, even though they are shown in differentdrawings. Also, in the description of embodiments, detailed descriptionof well-known related structures or functions will be omitted when it isdeemed that such description will cause ambiguous interpretation of thepresent disclosure.

It should be understood, however, that there is no intent to limit thisdisclosure to the particular example embodiments disclosed. On thecontrary, example embodiments are to cover all modifications,equivalents, and alternatives falling within the scope of the exampleembodiments. Like numbers refer to like elements throughout thedescription of the figures.

In addition, terms such as first, second, A, B, (a), (b), and the likemay be used herein to describe components. Each of these terminologiesis not used to define an essence, order or sequence of a correspondingcomponent but used merely to distinguish the corresponding componentfrom other component(s). It should be noted that if it is described inthe specification that one component is “connected,” “coupled,” or“joined” to another component, a third component may be “connected,”“coupled,” and “joined” between the first and second components,although the first component may be directly connected, coupled orjoined to the second component.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used herein, thesingular forms “a,” “an,” and “the,” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willbe further understood that the terms “comprises,” “comprising,”“includes,” and/or “including,” when used herein, specify the presenceof stated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It should also be noted that in some alternative implementations, thefunctions/acts noted may occur out of the order noted in the figures.For example, two figures shown in succession may in fact be executedsubstantially concurrently or may sometimes be executed in the reverseorder, depending upon the functionality/acts involved.

Various example embodiments will now be described more fully withreference to the accompanying drawings in which at least one exampleembodiment are shown. In the drawings, the thicknesses of layers andregions are exaggerated for clarity.

Unless otherwise defined, all terms, including technical and scientificterms, used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this disclosure pertains. Terms,such as those defined in commonly used dictionaries, are to beinterpreted as having a meaning that is consistent with their meaning inthe context of the relevant art, and are not to be interpreted in anidealized or overly formal sense unless expressly so defined herein.

Hereinafter, examples are described in detail with reference to theaccompanying drawings. Like reference numerals in the drawings denotelike elements, and a known function or configuration will be omittedherein. The examples to be described hereinafter may be used for userverification or authentication. For example, the examples may be usedfor user verification to use a mobile device, such as, for example, asmartphone, a smart vehicle, and a smart home appliance, or used foruser verification to use electronic commerce (e-commerce). Based on aspecification required for an application for which user verification isneeded, accuracy in the user verification or a speed for performing theuser verification may be flexibly improved.

FIG. 1 is a diagram illustrating a user verification system according toat least one example embodiment. Referring to FIG. 1, an apparatus foruser verification, hereinafter simply referred to as a user verificationapparatus 110, may be embodied as a software module, a hardware module,or a combination thereof, and may receive a request for verification, ora verification request, from various applications and transmit aresponse to the verification request to the applications. The userverification apparatus 110 may generate a result of the verification bycomparing biometric information measured by various sensors andpre-registered biometric information, and transmit the generated resultas the response to the verification request. Although described indetail later, the user verification apparatus 110 may perform userverification using a plurality of biometric verifiers. The biometricverifiers may perform biometric verification of different modalities,and at least one biometric verifier may be a verifier that may output aresult of the verification through multiple stages.

As shown in FIG. 1, the user verification apparatus 110 may becommunicatively coupled (“connected”) to a device 190. In at least oneexample embodiment, the user verification apparatus 110 is includedwithin, as an element of, the device 190. As described further below,the device 190 may include an electronic device that may include a userinterface (e.g., a touchscreen display). In at least one exampleembodiment, the device 190 may be a vehicle (e.g., an automobile)configured to transport one or more users (“occupants”) through anenvironment.

The user verification apparatus 110 may include a plurality of biometricverifiers. Such biometric verifiers may be implemented by a processorexecuting a program of instructions stored on a memory. The userverification apparatus 110 may generate the result of the verificationby setting a termination stage of the at least one biometric verifierthat supports multi-stage biometric verification based on anapplication, and fusing outputs of the biometric verifiers based on theset termination stage. For convenience of description, an output of eachof the biometric verifiers is referred to as an individual verificationresult, and a result of fusing the outputs of the biometric verifiers isreferred to as a final verification result. For example, a result to beoutput from individual stages of the biometric verifier that supportsthe multi-stage biometric verification and a result to be output from abiometric verifier that does not support the multi-stage biometricverification may be an individual verification result, and the result tobe transmitted as the response to the verification request may be afinal verification result. As referred to herein, a final verificationresult includes information indicating, to a requesting application(e.g., 120/130/140), an identity associated with a user based onreceived biometric information.

Such a final verification result may be used for user verification invarious applications. Based on such user verification (e.g., verifying auser based on the final verification result, the user verificationapparatus 110 may generate an unlocking command signal. The unlockingcommand signal, as shown in FIG. 1, may be transmitted to device 190.The unlocking command signal may include a signal that includesinformation indicating that the user matches or substantially matches(“correlates”) with an enrolled user.

For example, a lock application 120 may be executed to cancel a lock ofa terminal based on the final verification result, and a micropaymentapplication 130 or a macropayment application 140 may be executed toperform online payment based on the final verification result. Althoughthe micropayment application 130 and the macropayment application 140will be described separately for convenience of description, themicropayment application 130 and the macropayment application 140 may beincluded in one online commerce application, or included in afunctionality of the online commerce application that is performed basedon a sum of money to be paid. At least some applications, including oneor more of the lock application 120, micropayment application 130, andthe macropayment application 140 may be implemented externally to adevice (e.g., an electronic device and/or vehicle) implementing the userverification apparatus 110, including applications executed on a remoteserver and in communication with a device implementing the userverification apparatus 110 via a communication interface. Such acommunication interface may be included in a device implementing(“including”) the user verification apparatus 110.

The applications may have different verification characteristics basedon a type of an application. For example, the lock application 120 mayrequire a high verification speed despite a relatively low securitylevel. The micropayment application 130 may require a middleverification speed and a middle security level, and the macropaymentapplication 140 may require a high security level despite a lowverification speed. Here, the terms “high,” “middle,” and “low” levelsare used to indicate three different security levels, and do notindicate absolute values of the levels. When a security level increases,accuracy or reliability of the final verification result may beimproved, although an amount of time used for obtaining the finalverification result may increase. Although the security level may bedetermined based on a type of an application, different security levelsmay be set for applications of the same type due to various variables,such as, for example, settings by a user and a surrounding environment.As referred to herein, “security level” of a verification result refersto a confidence level associated with an identification of a userprovided in the final verification result. In addition, as referred toherein, “verification speed” refers to a permitted period of elapsedtime from the transmission of the verification request until theverification result is received at the requesting application. In atleast one example embodiment, a verification request that is received atthe user verification apparatus 110 from an application may includeparameter information indicating at least one of a specified thresholdFAR, a specified threshold verification speed, and/or a specifiedthreshold security level to be associated with a final verificationresult that is provided by the user verification apparatus 110 inresponse to the verification request. In at least one exampleembodiment, the user verification apparatus 110 may store informationassociating a given application with at least one of a specifiedthreshold FAR, a specified threshold verification speed, and/or aspecified threshold security level to be associated with a finalverification result that is provided by the user verification apparatus110 in response to receiving the verification request from theapplication at the user verification apparatus 110. In at least oneexample embodiment, a particular security level may be associated, atthe user verification apparatus 110, with a particular verificationrequest received at the user verification apparatus 110 from anapplication, based on one or more of the a “type” associated with theapplication, user-initiated settings, information associated with asurrounding environment, or the like.

The user verification apparatus 110 may adjust a verification speed oraccuracy based on verification characteristics of applications. Forexample, when there is a single biometric verifier that supports themultiple stages, a verification performance and a verification speed maybe determined by a combination of a termination stage of the biometricverifier and another biometric verifier. For another example, wherethere is a plurality of biometric verifiers that supports the multiplestages, a verification performance and a verification speed may bedetermined by a combination of a plurality of termination stages. Asreferred to herein, “verification performance” and “verificationaccuracy” are parameters expressing control of the verifiers ofapparatus 110 to provide a verification result that meets a specified“security level” and/or “verification speed” corresponding to a FARassociated with a verification request from an application.

In detail, for example, when a false acceptance rate (FAR) required forthe lock application 120 is 1/50 kilo (K), the user verificationapparatus 110 may perform verification based on the FAR, and provide aresponse for a relatively short period of time, for example, 145milliseconds (ms). The user verification apparatus 110 may determine atermination stage or a combination of termination stages that satisfiesthe FAR of 1/50K. For example, when a combination of a lowest-levelstage of a first biometric verifier among the biometric verifiers and alowest-level stage of a second biometric verifier among the biometricverifiers satisfies the FAR of 1/50K and has a highest verificationspeed, the user verification apparatus 110 may set a first stage of thefirst biometric verifier to be a termination stage of the firstbiometric verifier, and set a first stage of the second biometricverifier to be a termination stage of the second biometric verifier. Asreferred to herein, a “security level” may be indicated by a “falseacceptance rate (FAR)” and/or “verification rate (VR)” parameterassociated with a verification request.

For another example, the micropayment application 130 may require an FARof 1/300K for a higher level of security compared to the lockapplication 120. The user verification apparatus 110 may set a stage ata higher level than the lowest-level stage to be the termination stageof the first biometric verifier, the termination stage of the secondbiometric verifier, or the termination stages of the two biometricverifiers, and may then transmit a final verification result thatsatisfies the FAR of 1/300K. In such an example, the user verificationapparatus 110 may provide a response at, for example, 225 ms. Similarly,the macropayment application 140 may require a lower FAR compared to themicropayment application 130. The user verification apparatus 110 mayset a highest-level stage to be the termination stage of the firstbiometric verifier, the termination stage of the second biometricverifier, or the termination stages of the two biometric verifiers, andmay then transmit a final verification result that satisfies an FAR of1/1 mega (M). In such an example, the user verification apparatus 110may provide a response at, for example, 315 ms. The biometric verifiersmay be controlled, based on setting and/or re-setting the terminationstages of one or more biometric verifiers, to control the “verificationperformance/accuracy” and/or the “verification speed” associated with averification result to meet parameters associated with a receivedverification request, including a specified threshold FAR associatedwith the verification request. In at least one example embodiment,verification performance and verification speed are inversely related.

As described above, the user verification apparatus 110 may dynamicallyadjust a security level using the biometric verifiers. The biometricverifiers may perform biometric verification of different modalities,respectively, and thus multi-verification may be enabled and thesecurity level may be improved.

In at least one example embodiment, the user verification apparatus 110may include a memory storing a program of instructions and a processorconfigured to executed the stored program of instructions to implementone or more functions of the user verification apparatus 110.

In at least one example embodiment, one or more of the lock application120, micropayment application 130, and macropayment application 140 maybe implemented based on a processor executing a program of instructionsstored on a memory. Such a processor and/or memory may be common with aprocessor and/or memory at least partially comprising and/orimplementing the user verification apparatus 110.

In at least one example embodiment, the biometric informationillustrated and described with reference to FIG. 1 is received from abiometric sensor device that is external to the user verificationapparatus 110. As shown in FIG. 1, the biometric sensor device fromwhich biometric information is received may be external to the userverification system. The user verification apparatus 110 and thebiometric sensor device may be located in a common apparatus (e.g., anelectronic device, a vehicle, some combination thereof, or the like) orseparate apparatuses. In at least one example embodiment, differenttypes of biometric information (e.g., fingerprint biometric information,facial recognition biometric information, etc.) may be received at theuser verification apparatus 110 from separate, respective biometricsensor devices.

In at least one example embodiment, at least a portion of the userverification system shown in FIG. 1, including the user verificationapparatus 110, may be implemented in a device 190 that is an electronicdevice, e.g., based on a processor executing a program of instructionsstored on a memory. The electronic device may include a cellphone, atablet computer, a wearable device, and the like. In at least oneexample embodiment, at least a portion of the user verification systemshown in FIG. 1, including the user verification apparatus 110, mayinclude a chip in a cellphone, a tablet computer, a wearable device, orthe like.

In at least one example embodiment, at least a portion of the userverification system shown in FIG. 1, including the user verificationapparatus 110 may be included in a device 190 that is an electronicdevice, including one or more cellphones, tablet computers, wearabledevices, and the like, such that the electronic device is configured toperform biometrics-based verification or authentication. Thus, the userverification system may configure an electronic device to provideimproved user security with regard to electronic device functionalityaccess and/or control.

In at least one example embodiment, in response to a determination thata user is verified based on the verification result, the userverification apparatus 110 may generate an unlocking command signal thatincludes a command to at least partially unlock, to access by theverified user, a device 190 that is an electronic device. Unlocking adevice 190 that is an electronic device may include commanding thedevice 190 to enable user access to at least a portion of the device 190through user interaction with one or more user interfaces of and/orcoupled to the device 190. In at least one example embodiment, inresponse to a determination that the user is verified, the userverification apparatus may generate an unlocking command signal thatincludes a command to assign a right to access a desired (and/or,alternatively, predetermined) function of the device 190 to the user.

In at least one example embodiment, at least a portion of the userverification system shown in FIG. 1, including the user verificationapparatus 110 may be included in a device 190 that is a vehicle,including an automobile, a watercraft, an aircraft, or the like, suchthat the vehicle is configured to perform biometrics-based verificationor authentication for vehicle security. For example, a vehicle thatincludes the user verification apparatus 110 may be configured toperform a facial verification operation based on a driver of a vehicleapproaching the vehicle within a certain threshold distance from thevehicle. The vehicle may be further configured to subsequently perform afingerprint verification operation when the driver grabs a door handleof the vehicle. As a result, the vehicle may be configured toselectively unlock access to and/or functions of the vehicle to thedriver based on the performed operations. Thus, the user verificationsystem may configure a vehicle to provide improved driver/user/occupantsecurity and/or safety with regard to vehicle access and/or control.

In at least one example embodiment, in response to a determination thata user is verified based on the verification result, the userverification apparatus 110 may generate an unlocking command signal thatincludes a command to at least partially unlock, to access by theverified user, a device 190 that is a vehicle. Unlocking a device 190that is a vehicle via an unlocking command signal may include commandingthe device 190 to selectively grant, to the verified user, access to aninterior of the vehicle based on the verifying (e.g., unlocking one ormore particular doors, hatches, etc. of the vehicle). Unlocking a device190 that is a vehicle via an unlocking command signal may includecommanding the device 190 to selectively grant, to the verified user,control over one or more driving elements (“driving controls”) of thevehicle (e.g., vehicle throttle control, vehicle steering control,vehicle navigation control, vehicle engine startup/shutdown control,etc.) based on the verifying.

FIG. 2 is a diagram illustrating a user verification apparatus accordingto at least one example embodiment. Referring to FIG. 2, the userverification apparatus includes a controller 210, a plurality ofbiometric verifiers, for example, a first biometric verifier 220 and asecond biometric verifier 230, and a fusion model 240. Each of thebiometric verifiers 220 and 230 may perform biometric verification usingbiometric information of a user, and the fusion model 240 may generateinformation for user verification by fusing outputs of the biometricverifiers 220 and 230. Each of the biometric verifiers 220 and 230 mayinclude multiple stages. For example, the first biometric verifier 220may include n stages, and the second biometric verifier 230 may includem stages. In at least one example embodiment, each of the elementsillustrated in FIG. 2 may be implemented by a processor executing aprogram of instructions stored in a memory.

In at least one example embodiment, each biometric verifier of the firstand second biometric verifiers 220 and 230 may be configured to performa verification process that may terminate at one of various stages,where each stage corresponds to a particular “verification performance”and/or “verification accuracy” of the verification result output by theverifier to correspond to a specified security level. Each stage may bean intermediate or final step in a sequence of verification operationsperformed on biometric input information, where the output of eachintermediate stage is input to the next stage, and where the output of aselected termination stage may be output as the verification result ofthe verifier.

In at least one example embodiment, each biometric verifier may beimplemented as (e.g., may include) a neural network, and each stage maycorrespond to a layer of the neural network. In at least one exampleembodiment, verification performance may be proportional, andverification speed may be inversely proportional, to the level of thelayer from which a verifier outputs a verification result. For example,the higher or upper layer from which a verification result is output,the more improved verification performance and the more reducedverification speed may be obtained.

When the number of stages increases, an amount of time used forverification may also increase although accuracy in the verification maybe improved. The controller 210 may set at least one termination stagethat outputs an individual verification result. For example, asillustrated in FIG. 2, the controller 210 sets, to be the terminationstage, a first stage of the first biometric verifier 220 and a secondstage of the second biometric verifier 230. In an example illustrated inFIG. 2, it is assumed that the two biometric verifiers 220 and 230 areused, and both the two biometric verifiers 220 and 230 support themultiple stages. However, such an example may be applicable to a casewhere three or more biometric verifiers are used and only a portion ofthe multiple biometric verifiers supports the multiple stages.

The controller 210 may set the termination stage of the biometricverifiers 220 and 230 based on a particular (or, alternatively,predetermined) criterion including at least one of an application type,a security level, a sensing environment, main verification or auxiliaryverification, and a selection by a user. For example, when a securitylevel of an application is high, the controller 210 may set a level ofthe termination stage to be high. When the level of the terminationstage increases, an amount of time used for outputting an individualverification result may increase although accuracy of the individualverification result may be improved. Thus, when accuracy in verificationis relatively important, the level of the termination stage may be setto be higher. In contrast, when a speed of the verification isrelatively important, the level of the termination stage may be set tobe lower. Accuracy and a speed for final verification may be determinedby both the termination stage (or a first termination stage) of thefirst biometric verifier 220 and the termination stage (or a secondtermination stage) of the second biometric verifier 230, and thecontroller 210 may select a combination of the first termination stageand the second termination stage that satisfies verification accuracyand a verification speed that are required by an application. In atleast one example embodiment, setting a termination stage of a biometricverifier includes configuring the verifier to provide the outputinformation of the set stage as the verification result of the biometricverifier.

The controller 210 may set, to be the termination stage, a stage atwhich a verification rate (VR) and an FAR are satisfied based on thecriterion among the multiple stages of the biometric verifiers 220 and230. For an application, a VR and an FAR may be preset based on asecurity level. The application may provide the preset VR and FAR to thecontroller 210 and the controller 210 may set, to be the terminationstage, a stage at which the VR and the FAR of the application aresatisfied. In at least one example embodiment, each stage of a givenverifier may be associated with a particular FAR and VR. In at least oneexample embodiment, a combination of outputs from a particularcombination of verifiers at particular set termination stages may beassociated with a particular FAR/VR, such that the particularcombination may be selected by the controller upon a determination beingmade, at the user verification apparatus, that a verification request isassociated with the particular FAR/VR.

According to at least one example embodiment, the controller 210 maydetermine a combination of termination stages in which a VR and an FARrequired by an application are satisfied using a lookup table in whichVRs and FARs based on combinations of termination stages are stored, andset termination stages of the multiple biometric verifiers. In such acase, a VR and an FAR for each of combinations of the stages of thefirst verifier 220 and the stages of the second biometric verifier 230may be calculated in advance. In at least one example embodiment, acombination of termination stages for a particular combination ofbiometric verifiers may be set, at the user verification apparatus(e.g., by the controller 210) based on determining a VR and FARassociated with a verification request from an application. In at leastone example embodiment, an association of termination stage combinationsand VR/FARs may be stored in a lookup table and accessed by thecontroller 210 based on receiving, at the user verification apparatus,VR/FAR data associated with a verification request. Thus, the controller210 may determine which termination stages to set for the verifiersbased on the receipt of a verification request.

For example, in a case that an application requires a VR of 95% and anFAR of 1/50K, and a VR and an FAR are 90% and 1/50K, respectively, whena first stage of the first biometric verifier 220 and a second stage ofthe second biometric verifier 230 are set to be the termination stages,and a VR and an FAR are 98% and 1/50K, respectively, when the firststage of the first biometric verifier 220 and a second stage of thesecond biometric verifier 230 are set to be the termination stages, thecontroller 210 may set the first stage of the first biometric verifier220 and the second stage of the second biometric verifier 230 to be thetermination stages.

The biometric verifiers 220 and 230 may operate in parallel or inseries. That is, the first biometric verifier 220 and the secondbiometric verifier 230 may operate simultaneously during a time sectionT1, or operate in order during a time section T1 and a time section T2.

The biometric verifiers 220 and 230 may perform biometric verificationof different modalities. That is, the first biometric verifier 220 mayperform biometric verification using first modality biometricinformation of a user, and the second biometric verifier 230 may performbiometric verification using second modality biometric information ofthe user. For example, each of the biometric verifiers 220 and 230 mayperform biometric verification using any one of a face, a fingerprint,an iris, a vein, palm lines, a shape of an ear, and an electrocardiogram(ECG). Since a plurality of pieces of biometric information is used,accuracy in verification may be improved, although the level of thetermination stage is set to be lower, compared to using a single pieceof the biometric information. In at least one example embodiment,performing biometric verification of different “modalities” includesperforming biometric verification using different “modality” biometricinformation of a user, where each “modality” of biometric informationrefers to different “types” and/or “classes” of biometric information.Different types/classes of biometric information may include, forexample, fingerprints, irises, ECGs, and face images. In at least oneexample embodiment, performing biometric verification of differentmodalities includes performing biometric verification of differentsets/combinations of biometric input information. In at least oneexample embodiment, performing biometric verification associated withdifferent modalities may include determining that the number(“quantity”) of all stages of a biometric verifier is different for eachverifier and a verification method to be performed by a biometricverifier is different from each biometric verifier, and thus setting thetermination stages of the respective biometric verifiers accordingly. Inat least one example embodiment, the biometric information to be inputto a biometric verifier is different for each biometric verifier, asshown in the biometric verifier illustrated in FIG. 5 and the biometricverifier illustrated in FIG. 8.

The fusion model 240 may generate a final verification result for theuser verification by fusing individual verification results output atthe respective termination stages of the biometric verifiers 220 and230, and the controller 210 may verify a user using an output of thefusion model 240. For example, the controller 210 may determine whetherbiometric information measured by a sensor corresponds to biometricinformation of a pre-registered user using the final verificationresult.

The fusion model 240 may include individual models corresponding tovarious combinations of the termination stages of the biometricverifiers 220 and 230. For example, when each of the biometric verifiers220 and 230 includes three stages, the number of combinations of thestages may be nine and the fusion model 240 may include individualmodels prepared in advance corresponding respectively to the ninecombinations. The controller 210 may set the respective terminationstages of the biometric verifiers 220 and 230, and select an individualmodel corresponding to the set termination stages among the individualmodels included in the fusion model 240. For example, as illustrated inFIG. 2, the controller 210 may select, from the individual models, anindividual model corresponding to the first stage of the first biometricverifier 220 and the second stage of the second biometric verifier 230.The selected individual model may generate information for the userverification by fusing the individual verification results of thebiometric verifiers 220 and 230. A detailed description of a fusionmodel will be provided with reference to FIGS. 3 and 4. In at least oneexample embodiment, a “fusion model” is a particular model that isselected at the user verification apparatus (e.g., by controller 210)based on a selected combination of biometric verifiers and correspondingset termination stages thereof from which verification results are inputto the fusion model. In some example embodiment, the selected fusionmodel is executed to (e.g., is configured to) “fuse” the verificationresults of the biometric verifiers to generate a fused verificationresult as the final verification result.

Although the biometric verifiers 220 and 230 and the fusion model 240are illustrated separately from the controller 210 in FIG. 2, thebiometric verifiers 220 and 230 and the fusion model 240 may operate inthe controller 210.

FIG. 3 is a diagram illustrating a fusion model 330 according to atleast one example embodiment. Referring to FIG. 3, the fusion model 330includes a plurality of models corresponding to combinations oftermination stages of multiple biometric verifiers, for example, a firstbiometric verifier 310 and a second biometric verifier 320, and outputsa final verification result based on individual verification resultsreceived from the biometric verifiers 310 and 320. To output the finalverification result, each of the models included in the fusion model 330may classify an input vector including the individual verificationresults of the biometric verifiers 310 and 320, and thus the finalverification result may also be referred to as a classification result.In at least one example embodiment, a fusion model includes a set ofmultiple sub-models, where each given sub-model corresponds to aparticular combination of verifiers and particular set terminationstages thereof.

For example, when the first biometric verifier 310 includes n stages andthe second biometric verifier 320 includes m stages, the fusion model330 may include n×m individual models. Hereinafter, an example of avalue of n being 3 and a value of m being 3 (n=m=3) will be described.However, the values of n and m are not limited to the example. In suchan example of the value of n being 3 and the value of m being 3, a firstmodel of the fusion model 330 may correspond to a first stage of thefirst biometric verifier 310 and a first stage of the second biometricverifier 320, and a second model of the fusion model 330 may correspondto the first stage of the first biometric verifier 310 and a secondstage of the second biometric verifier 320. Similarly, a ninth model ofthe fusion model 330 may correspond to a third stage of the firstbiometric verifier 310 and a third stage of the second biometricverifier 320.

In at least one example embodiment, each fusion model may be trained togenerate a final verification result according to a particular set of“n” verifiers having “m” set termination stages using training data,where the training data includes sets of biosignals for different usersand sets of biosignals for a common user. The fusion model may betrained to generate verification result information that correctlyidentifies the sets of biosignals as either corresponding to a commonuser or different users.

The individual models may be trained, in advance, based on correspondingstages. Each of outputs of the biometric verifiers 310 and 320 may berepresented as a vector, and the fusion model 330 may be trained basedon a combination of the vectors. Each of the models included in thefusion model 330 may be a support vector machine (SVM). For example, thefirst model may be trained based on a combination of an output vector ofthe first stage of the first biometric verifier 310 and an output vectorof the first stage of the second biometric verifier 320. The secondmodel may be trained based on a combination of the output vector of thefirst stage of the first biometric verifier 310 and an output vector ofthe second stage of the second biometric verifier 320.

The fusion model 330 may be trained using training data including pairsof biosignals having a same label and pairs of biosignals havingdifferent labels. The same label indicates a same user, and thedifferent labels indicate different users.

Hereinafter, a process of training the first model of the fusion model330 is described in detail. In the training of the first model, thefirst biometric verifier 310 may receive a first biosignal having afirst label, and output a first vector through the first stage. Thefirst biometric verifier 310 may receive a second biosignal having thesame label, for example, the first label, and output a second vectorthrough the first stage. Based on a difference between the first vectorand the second vector, a first individual verification result of thefirst stage of the first biometric verifier 310 may be obtained. Here,an individual verification result may be represented as a verificationscore. Similarly, a third biosignal and a fourth biosignal having thefirst label may be applied to the second biometric verifier 320, and asecond individual verification result of the first stage of the secondbiometric verifier 320 may be obtained. Using pairs of biosignals havingthe same label, the fusion model 330 may be trained to classify, intotrue of a true or false method, a first input vector including the firstindividual verification result of the first stage of the first biometricverifier 310 and the second individual verification result of the firststage of the second biometric verifier 320.

In addition, in the training of the first model, a third individualverification result of the first stage of the first biometric verifier310 may be obtained by applying, to the first biometric verifier 310, afifth biosignal having the first label and a sixth biosignal having alabel different from the first label, for example, a second label.Similarly, a fourth individual verification result of the first stage ofthe second biometric verifier 320 may be obtained by applying, to thesecond biometric verifier 320, a seventh biosignal having the firstlabel and an eighth biosignal having the second label. In such a case,using pairs of biosignals having different labels, the fusion model 330may be trained to classify, into false of the true or false method, asecond input vector including the third individual verification resultof the first stage of the first biometric verifier 310 and the fourthindividual verification result of the first stage of the secondbiometric verifier 320.

The remaining models of the fusion model 330, for example, the secondmodel through the ninth model, may be trained in the same method that isapplied to the first model. Thus, each of the first through ninth modelsmay have a characteristic corresponding to a combination of the stagesincluded in the biometric verifiers 310 and 320, and may output a finalverification result based on the individual verification results outputfrom the biometric verifiers 310 and 320. The first through ninth modelsmay be trained with different training samples to be output fromdifferent termination stages, and may thus have differentcharacteristics. For example, the first through ninth models may havedifferent VRs. In detail, since the first model is trained based on theindividual verification results of the first stages of the biometricverifiers 310 and 320, the first model may have a lower VR than theninth model that is trained based on individual verification results ofthe third stages of the biometric verifiers 310 and 320.

FIGS. 4A and 4B are diagrams illustrating a VR and an FAR of a fusionmodel according to at least one example embodiment. The graphs shown inFIGS. 4A-4B each show a distribution of quantities of samples of a pairof biosignals having various distances between feature values for thegiven samples for 1) biosignal pairs for identical objects and 2)biosignal pairs for non-identical objects. In at least one exampleembodiment, the samples in FIGS. 4A-4B are obtained from a fusion modelfor which training is completed. The VR and the FAR will be describedhereinafter with reference to the first through ninth models of thefusion model 330 illustrated in FIG. 3. FIG. 4A illustrates a graph 410indicating a result of verifying the first model, and FIG. 4Billustrates a graph 420 indicating a result of verifying the ninthmodel. Referring to the graphs 410 and 420, a graph associated withidentical objects may be obtained by applying a validation data pair forthe identical objects to the first model and the ninth model for whichtraining is completed, and a graph associated with non-identical objectsmay be obtained by applying a validation data pair for the non-identicalobjects to the first model and the ninth model. In the graphs 410 and420, an x axis indicates a distance among feature values obtained frompieces of validation data in the validation data pair, and a y axisindicates the number of samples corresponding to the distances, forexample, the validation data pairs. The graph associated with theidentical objects and the graph associated with the non-identicalobjects may be of a form of a normal distribution. Here, the identicalobjects indicate a same user, and the non-identical objects indicatedifferent users.

Referring to the graphs 410 and 420, the first through ninth models mayhave different performances in separating the graph associated with theidentical objects and the graph associated with the non-identicalobjects. For example, in the graph 410, when a threshold satisfying anFAR of 5% is set, a VR may be approximately 65%. In the graph 420, whena threshold satisfying an FAR of 5% is set, a VR may become close to100%. Here, the FAR of 5% indicates a rate at which only a result, forexample, a distance, included in an area corresponding to bottom 5% ofan entire area of the graph associated with the non-identical objects isallowed to be misrecognized to be the identical objects. In such a case,a VR may indicate a rate of an area corresponding to a distance lessthan or equal to the threshold set based on the FAR of 5% of an entirearea of the graph associated with the identical objects.

Similarly, according to at least one example embodiment, a controllermay calculate a VR of each of the first through ninth models based on aspecific FAR, and select, from a fusion model, an individual model thatsatisfies a VR and an FAR required by an application. For example, asillustrated in FIG. 3, when an application requires an FAR of 5% and aVR of 90%, the controller may select the third stage of the firstbiometric verifier 310 and the third stage of the second biometricverifier 320, and select the ninth model to be a fusion model.

In the example embodiments shown in FIGS. 4A-4B, the overlappingdistributions in each graph show the relationship between the VR and FARin a given model represented by the graph, where the verification rate(VR) corresponds to the proportion of the area of the identical objectdistribution that is less than or equal to a given x-axis value, and thecorresponding false acceptance rate (FAR) corresponds to the proportionof the area of the non-identical object distribution that is less thanor equal to the same x-axis value.

In the example embodiments shown in FIGS. 4A-4B, the graphs show thateach model can be associated with a particular relationship with VR andFAR, such that each model may be associated with a particular VR given arequired FAR.

In at least one example embodiment, including the example embodimentsshown in FIGS. 4A-4B, if and/or when a verification request from anapplication is determined to be associated with a particular FAR and VR,a particular fusion model that satisfies both of the particular VR andFAR may be identified and selected (e.g., by a controller of a userverification apparatus), such that the particular combination of “n”verifiers and hat termination stages associated with the selected fusionmodel may further be identified and selected.

FIG. 5 is a diagram illustrating a fingerprint verifier 510 according toat least one example embodiment. According to at least one exampleembodiment, a biometric verifier described above may be the fingerprintverifier 510 of FIG. 5. Referring to FIG. 5, the fingerprint verifier510 includes a first stage, a second stage, and a third stage, and eachof the stages outputs an individual verification result based on aninput fingerprint image corresponding to biometric information. Thefirst stage outputs an overlapping area and a matching score between aregistered fingerprint image and the input fingerprint image. Anoperation of the first stage will be described in detail with referenceto FIG. 6. In at least one example embodiment, a fingerprint verifiermay be implemented by a processor and memory, where the verifier isconfigured to receive a fingerprint image captured by a biometric sensordevice that is external to the verifier.

In at least one example embodiment, each successive stage of thefingerprint verifier 510 is configured to output verification resultinformation that provides matching scores for successively smallerblocks of a successively partitioned overlapping area between aregistered image and the input image. Thus, each successive stageprovides a verification result that verifies a match or mis-matchbetween the images with successively greater granularity.

FIG. 6 is a diagram illustrating a process of matching based on a changein an input fingerprint image according to at least one exampleembodiment. Here, the change may include scaling, rotation, translation,or various combinations thereof. When the input fingerprint image and aregistered fingerprint image are obtained through a same sensor, thescaling may be omitted.

In at least one example embodiment, a first stage of a fingerprint imageverifier may, upon receiving an input image and comparing the inputimage with a registered image associated with a registered user, rotate,translate, and/or scale the input image to increase and/or maximizematching (e.g., a maximum matching score) between the images.Information indicating the rotation, translation, and] or scaling of theinput image may be included in the output verification information ofthe first stage of the verifier. The resulting matching score may alsobe included as the output of the first stage (e.g., verification resultof the first stage). In at least one example embodiment, successivestages of the fingerprint image verifier may be implemented to partitionthe input image into blocks, match each block to one or more registeredimages, and calculate matching scores for each block that may beincluded in the verification result information of the given successivestages.

FIG. 6 illustrates an input fingerprint image 610 and a registeredfingerprint image 620. The input fingerprint image 610 and theregistered fingerprint image 620 may be obtained through a fingerprintrecognizing device, for example, a fingerprint sensor. The registeredfingerprint image 620 may be pre-stored in a database. A sensing area ofthe fingerprint sensor may be smaller than a size of a fingerprint of auser, and thus the input fingerprint image 610 and the registeredfingerprint image 620 may be a partial image including information aboutonly a portion of the fingerprint. To determine an overlapping area anda matching score between the input fingerprint image 610 and theregistered fingerprint image 620, rotation and translation may beperformed on the input fingerprint image 610.

The first stage may rotate and translate the input fingerprint image 610to overlap a shared area in the input fingerprint image 610 and a sharedarea in the registered fingerprint image 620. The first stage may matchthe input fingerprint image 610 and the registered fingerprint image 620using various methods. For example, the first stage may determinetranslation information and rotation information between the inputfingerprint image 610 and the registered fingerprint image 620 based ona frequency-based matching method. The frequency-based matching methodmay be a method of performing matching in a frequency domain.

The translation information between the input fingerprint image 610 andthe registered fingerprint image 620 may include an x-axis translationparameter Tx and a y-axis translation parameter Ty. In addition, therotation information between the input fingerprint image 610 and theregistered fingerprint image 620 may include a rotation parameter R.Here, Tx and Ty are also referred to as a translation, and R as arotation angle.

The first stage may translate and rotate the input fingerprint image 610based on the translation information and the rotation informationobtained as a result of the matching. The translation information andthe rotation information may be relative information between the inputfingerprint image 610 and the registered fingerprint image 620, and thusthe first stage may translate and rotate the registered fingerprintimage 620 instead of translating and rotating the input fingerprintimage 610.

The first stage may obtain the overlapping area and the matching scorebetween the input fingerprint image 610 and the registered fingerprintimage 620 after translating and rotating the input fingerprint image 610or the registered fingerprint image 620. For example, the matching scoremay be obtained based on an image brightness value-based normalizedcorrelation between the input fingerprint image 610 and the registeredfingerprint image 620. The first stage may output the obtainedoverlapping area and the obtained matching score. For convenience ofdescription, one registered fingerprint image is illustrated as theregistered fingerprint image 620. However, a plurality of registeredfingerprint images may be included in the database as the registeredfingerprint image 620. In such a case, the first stage may match theinput fingerprint image 610 and each of the registered fingerprintimages, and output an overlapping area and a matching score between theinput fingerprint image 610 and each of the registered fingerprintimages. The first stage may be processed within a relatively shortperiod of time compared to other stages. However, a VR based on anindividual verification result of the first stage may be lower comparedto VRs of the other stages.

The described operations of the first stage may be applicable tooperations of the second stage and the third stage. However, the secondstage and the third stage may further perform an operation ofpartitioning an input fingerprint image into a plurality of blocks andmatching each of the blocks to a registered fingerprint image. Referringback to FIG. 5, the second stage may partition an input fingerprintimage into a particular (or, alternatively, predetermined) number ofblocks, for example, three blocks. The second stage may output matchingscores between the three blocks and a registered fingerprint image. Inaddition, the third stage may partition the input fingerprint image intoa greater number of blocks, for example, five blocks, compared to thesecond stage, and output matching scores between the five blocks and aregistered fingerprint image. The operations of the second stage and thethird stage will be described in detail with reference to FIG. 7.

FIG. 7 is a diagram illustrating a process of partitioning an inputfingerprint image 720 and a process of matching according to at leastone example embodiment. Operations of the second stage to be describedhereinafter may be applicable to operations of the third stage.

In at least one example embodiment, a second (and or third, fourth,etc.) stage of a fingerprint verifier may be implemented to partitionthe input image into multiple blocks and match the individual blocks,with the rotation/translation/scaling information from the first block,to one or more stored registered images. A matching score for each blockwith regard to each utilized registered image may be determined based onthe matching.

Referring to FIG. 7, the second stage partitions the input fingerprintimage 720 into a plurality of blocks, for example, a block 721, a block722, and a block 723. The second stage may compare the blocks 721through 723 to registered fingerprint images 711 and 712, instead ofcomparing the input fingerprint image 720 to the registered fingerprintimages 711 and 712.

The second stage may partition the input fingerprint image 720 usingvarious methods. For example, the second stage may partition the inputfingerprint image 720 based on a preset pattern. The pattern may bedetermined in advance based on a shape and a size of a sensing area of afingerprint sensor, and a shape and a size of a registered partialimage. The pattern may dynamically change as necessary. Also, the inputfingerprint image 720 may be partitioned not to overlap the blocks 721through 723, or to overlap neighboring blocks among the blocks 721through 723 by a certain area. In at least one example embodiment,partitioning the input image into blocks results in a reducedoverlapping area between the input image and the registered image(s). Inat least one example embodiment, a ratio of the overlapping area betweenthe block and the registered image to a total area of the block may behigh, thereby improving matching accuracy.

Using the blocks 721 through 723, the second stage may have an improvedmatching efficiency. When the input fingerprint image 720 is input,partitioning the input fingerprint image 720 into a plurality of blocks,for example, the blocks 721 through 723, and performing matching may bemore effective because an overlapping area between the input fingerprintimage 720 and each of the registered fingerprint images 711 and 712 isnot large. A ratio of an overlapping area between the block 723 and theregistered fingerprint image 711 to an entire area of the block 723 maybe higher than a ratio of an overlapping area between the inputfingerprint image 720 and the registered fingerprint image 711 to anentire area of the input fingerprint image 720, and thus such ablock-based matching may be more accurately and effectively performed.

The second stage may match a block and a registered fingerprint image bytranslating and rotating the block, and calculate a matching score basedon an overlapping area between the block and the registered fingerprintimage. For example, as illustrated in FIG. 7, the second stage maycalculate matching scores of various combinations of the three blocks721 through 723 and the registered fingerprint images 711 and 712. Here,based on a result of the matching performed by the first stage, thesecond stage may use only a portion of registered fingerprint imagesthat is highly ranked based on the result of the matching performed bythe first stage, instead of using all the registered fingerprint imagesstored in a database. In at least one example embodiment, the firststage may identify (e.g., be implemented to identify) the registeredimages for which the matching scores with the entire input image are thegreatest scores, and such a limited selection of registered images maybe selected to be used in the second stage, such that the matchingbetween blocks and registered images is only performed with regard tothe limited selection of registered images that were associated with arelatively high matching score in the first stage, thereby reducingprocessing time in the second stage.

Using a method similar to the method applied to the second stage, thethird stage may partition the input fingerprint image 720 into fiveblocks, and calculate a matching score of each of the five blocks. Thethird stage may output highly ranked K scores by arranging the matchingscores of the five blocks. In addition, the third stage may output afeature value of a plurality of matching scores. Here, the feature valuerefers to a value indicating a feature associated with the matchingscores, for example, a statistical value such as a mean value. Forexample, the third stage may output a mean value of top three matchingscores along with the top three matching scores among the matchingscores of the five blocks. The third stage may improve accuracy in userverification using such a feature value. Based on a result of thematching performed by the second stage, the third stage may use only aportion of registered fingerprint images that is highly ranked based onthe result of the matching performed by the second stage, instead ofusing all the registered fingerprint images stored in the database. Inat least one example embodiment, the third and successive stages of afingerprint verifier may operate similarly to the second stage, wherethe input image is successively partitioned into a greater quantity ofsmaller blocks, and the smaller blocks are matched with the limitedselection of registered images. Successive stages may use successivelymore limited selections of registered images, using the most highlymatching registered images from the preceding stages.

In at least one example embodiment, the second and/or third stage mayoutput “K scores” and/or a “feature value” of a plurality of matchingscores of the blocks matched in the given stage. In at least one exampleembodiment, a “feature value” is a value that is associated with thecombination of matching scores of the blocks. For example, the featurevalue may be an arithmetic mean value of the multiple matching scores ofthe blocks matched in the given stage. The feature value may beassociated with a limited selection of the matching scores of theblocks, including being a value associated with the top three matchingscores of five blocks.

FIG. 8 is a diagram illustrating a face verifier 810 according to atleast one example embodiment. According to an example embodiment, abiometric verifier described above may be the face verifier 810.Referring to FIG. 8, the face verifier 810 includes a first stage, asecond stage, and a third stage, and each of the stages may output anindividual verification result based on an input image, for example, aface image, corresponding to biometric information. The face verifier810 may output an individual verification result of each layer bycomparing features to be output by a plurality of layers in a neuralnetwork in response to the input image and features of a pre-storedregistered image corresponding to the layers. The stages included in theface verifier 810 may correspond to the layers, respectively. A processof outputting an individual verification result will be described withreference to FIG. 9.

In at least one example embodiment, the face verifier 810 may beconfigured to output verification result information according to aselected stage, where the verification information generated by anintermediate stage may be provided to a subsequent stage as input datato the subsequent stage.

In at least one example embodiment, the face verifier 810 may beconfigured to operate in a neural network having a plurality of layers,where each separate layer may perform a particular processing of theinput image and the outputs of different layers may correspond toseparate stages, such that an output from a selected termination stagemay correspond to an output of one or more particular layers of theneural network.

FIG. 9 is a diagram illustrating a plurality of layers included in aface verifier according to at least one example embodiment. Hereinafter,a description will be provided with reference to the first through thirdstages included in the face verifier 810 of FIG. 8. Referring to FIG. 9,the face verifier 810 includes a first layer 910, a second layer 920,layer 3-1 931, layer 3-2 932, and layer 3-3 933. The first layer 910,the second layer 920, and the layers 931 through 933 may be trained inadvance to output a feature value of the input image. The face verifier810 may be trained in advance to output an individual verificationresult based on a distance between the feature value of the input imageoutput from the first layer 910, the second layer 920, and the layers931 through 933, and a feature value of a pre-registered image.Although, in FIG. 9, a third layer includes the layers 931 through 933connected in parallel with the second layer 920, a neural network invarious structures other than the structure illustrated in FIG. 9 may beapplicable.

In at least one example embodiment, a face verifier includes multiple“layers” that each represent a particular processing of one or moreportions of the input image, where one or more layers may correspond toone or more “stages” of the verifier, such that an output of a layercorresponding to the selected termination stage is provided as theverification result information of the verifier.

In at least one example embodiment, the verification result output fromeach layer is at least one feature value associated with the inputimage. In at least one example embodiment, each “stage” of the verifiermay be implemented to compare a feature value “output” from thecorresponding layer to a corresponding stored feature value of theregistered image, and the corresponding stored feature value of theregistered image may be a feature value output by the correspondinglayer when the registered image is processed by the layer. In at leastone example embodiment, the verifier may output a given verificationresult indicating a determined distance between the feature value of theinput image and a feature value of a registered image. In at least oneexample embodiment, such a distance value may be represented as a“matching score.”

The first layer 910 may output a first feature value of the input imagebased on the input image. The first stage of the face verifier 810 maycompare the first feature value of the input image to a first featurevalue of the registered image, and output a first individualverification result based on a distance between the first feature valueof the input image and the first feature value of the registered image.The first individual verification result may be a verification score.The first feature value of the registered image may be output in advanceby the first layer 910, and stored in a database. Similarly, the secondstage may output a second individual verification result using thesecond layer 920. The second layer 920 may be a layer higher than thefirst layer 910, and thus the second individual verification resultbased on a second feature value of the input image may have a higher VRthan the first individual verification result based on the first featurevalue of the input image.

The third stage may output a third individual verification result usingthe layers 931 through 933. The layer 3-1 931, the layer 3-2 932, andthe layer 3-3 933 may output feature value 3-1 of the input image,feature value 3-2 of the input image, and feature value 3-3 of the inputimage, respectively. The third stage of the face verifier 810 maycompare the feature value 3-1 of the input image, the feature value 3-2of the input image, and the feature value 3-3 of the input image tofeature value 3-1 of the registered image, feature value 3-2 of theregistered image, and feature value 3-3 of the registered image, andoutput the third individual verification result based on a distancebetween the feature values.

At the first and second stages, the first feature value and the secondfeature value of the registered image may be feature values associatedwith an entire face of a user. In such a case, the first and secondstages may output the individual verification results based on theentire face of the user.

At the third stage, the feature value 3-1 of the registered image may bea feature value associated with the entire face of the user, and thefeature value 3-2 and the feature value 3-3 of the registered image maybe feature values associated with a portion of the face of the user, forexample, an eye, a nose, lips, or an ear of the user. The third stagemay output the individual verification result based on both the entireface of the user and the portion of the face of the user. Thus, thethird individual verification result of the third stage may have ahigher VR than the first and second individual verification results.

The first through third individual verification results may includematching scores between the feature values of the input image and thefeature values of the registered image. The third individualverification result may include a plurality of matching scoresassociated with the entire face and the portion of the face. Inaddition, the third individual verification result may also include astatistical value, for example, a mean value, of the matching scores.For example, the third stage may output a matching score of the face, amatching score of a first portion of the face, a matching score of asecond portion of the face, and also a mean value of the matchingscores. The third stage may improve accuracy in user verification usingthe matching scores and the statistical value.

In at least one example embodiment, a given stage may compare multiplefeature values from multiple, parallel layers with multiplecorresponding feature values of the registered image. In at least oneexample embodiment, a verification result from a given stage of thefacial verifier includes a matching score generated based on thecomparison of the feature values of the input image and the registeredimage, where the matching score represents a distance between thefeature values. Such matching scores may be accompanied by statisticalvalues associated with the matching scores.

As described above, an individual verification result of each of aplurality of biometric verifiers may be expressed by a vector. Theindividual verification result may have a dimension corresponding to thenumber of output values. For example, the third stage of the fingerprintverifier 510 of FIG. 5 may output top three matching scores among thematching scores of the five blocks, along with a mean value of the topthree matching scores. In such an example, an individual verificationresult of the third stage of the fingerprint verifier 510 may berepresented by a 4-dimension vector. Similarly, the third stage of theface verifier 810 of FIG. 8 may output three matching scores associatedrespectively with the face, and the first portion and the second portionof the face, along with a mean value of the three matching scores. Insuch an example, an individual verification result of the third stage ofthe face verifier 810 may be represented by a 4-dimension vector. Afusion model may receive the 4-dimension vector from each of thefingerprint verifier 510 and the face verifier 810 and receive, as aninput, an 8-dimension vector by a combination of the two 4-dimensionvectors. In at least one example embodiment, the fusion model maygenerate a final verification result based on the multi-dimensionalvector received from a combination of the vectors from the verifiers.

In at least one example embodiment, the fusion model may be implementedto combine the vectors to determine a matching score corresponding tothe combination of the input images provided to the multiple vector, andwhere the fusion model determines whether the identity associated withthe input images is the identity of a registered user associated withthe registered images based on a determination that the matching scoreat least meets a threshold that is associated with the required FAR/VRof the verification request. A fusion model may be, for example, an SVM,that is trained to receive an n-dimension vector as an input and outputa final verification result.

The fusion model may output a final verification result from the8-dimension vector. As described above, the fusion model may be, forexample, an SVM trained to output the final verification result byreceiving the 8-dimension vector as an input. Although an operation ofthe fusion model based on the combination of the third stage of thefingerprint verifier 510 and the third stage of the face verifier 810 isdescribed herein, the fusion model may include individual modelscorresponding to combinations of all stages and the individual modelsmay be trained in advance to output a final verification result whenindividual verification results are input.

FIG. 10 is a diagram illustrating a main verifier and a sub-verifieraccording to at least one example embodiment. Referring to FIG. 10, acontroller 1010 determines a main verifier 1020 and a sub-verifier 1030among a plurality of biometric verifiers. The main verifier 1020 is averifier mainly used for user verification, and the sub-verifier 1030 isa verifier additionally used for the user verification. For example, thecontroller 1010 may select, from various combinations of a terminationstage of the main verifier 1020 and a termination stage of thesub-verifier 1030, a combination that may increase a level of thetermination stage of the main verifier 1020. For example, a combinationthat allows the main verifier 1020 to output an individual verificationresult at an n-th stage, and the sub-verifier 1030 to output anindividual verification result at a first stage may be selected from thecombinations. A fusion model 1040 may output a final verification resultbased on individual verification results of the main verifier 1020 andthe sub-verifier 1030.

Alternatively, the controller 1010 may determine a stage of the mainverifier 1020 and a stage of the sub-verifier 1030 based on selectioninformation. The selection information may include a minimum requiredstage of the main verifier 1020 and a maximum required stage of thesub-verifier 1030. The controller 1010 may determine, to be atermination stage, a stage upper than or equal to the minimum requiredstage of the main verifier 1020 and a stage lower than or equal to themaximum required stage of the sub-verifier 1030.

The controller 1010 may determine the main verifier 1020 and thesub-verifier 1030 based on a particular (or, alternatively,predetermined) criterion including at least one of an application type,a security level, a sensing environment, main verification or auxiliaryverification, and a selection by a user. For example, when an intensityof illumination is low, a performance of a face recognizer maydeteriorate and the controller 1010 may thus set a fingerprintrecognizer to be the main verifier 1020 and the face recognizer to thesub-verifier 1030. Alternatively, to increase accuracy of the facerecognizer when the intensity of illumination is low, the controller1010 may set the face recognizer to be the main verifier 1020 andincrease a level of a termination stage of the face recognizer. Foranother example, when a degree of humidity is high, a performance of thefingerprint recognizer may deteriorate and the controller 1010 may thenset the face recognizer to be the main verifier 1020 and the fingerprintrecognizer to be the sub-verifier 1030. Alternatively, to increaseaccuracy of the fingerprint recognizer when the degree of humidity ishigh, the controller 1010 may set the fingerprint recognizer to be themain verifier 1020 and increase a level of a termination stage of thefingerprint recognizer.

In at least one example embodiment, a controller may select a “main”verifier and “sub-verifier” based on a desired level of the terminationstages of the selected verifiers, where the “main verifier” isidentified as the verifier having a higher level of termination stagethan the sub-verifier. In at least one example embodiment, if and/orwhen two verifiers have a common level of the termination stage, one ofthe two verifiers may be set as a main verifier and the other may be setas a sub-verifier.

In at least one example embodiment, the stages of the verifiers may bedetermined based on a main verifier and the where the informationspecifies a minimum and/or maximum stage of one or more particularverifiers. In at least one example embodiment, the selection informationmay be associated with a particular FAR/VR that is associated with areceived verification request.

In at least one example embodiment, a limited selection of verifiers maybe selected based on a set of criteria values. The criteria values maybe determined based on sensor input, user input, parameters associatedwith an application from which a verification request is received, somecombination thereof, or the like.

FIG. 11 is a flowchart illustrating a user verification method accordingto at least one example embodiment. The method illustrated in FIG. 11may be implemented by a single apparatus, including the userverification apparatus 110 illustrated in FIG. 1. Referring to FIG. 11,in operation 1110, a user verification apparatus sets a terminationstage of at least one of a plurality of biometric verifiers. Inoperation 1120, the user verification apparatus selects a fusion modelthat fuses outputs of the biometric verifiers based on the settermination stage. In operation 1130, the user verification apparatusverifies a user using the outputs of the biometric verifiers and thefusion model. The descriptions provided with reference to FIGS. 1through 10 may be applicable to the operations described with referenceto FIG. 11, and thus a more detailed description will be omitted here.

FIG. 12 is a diagram illustrating an electronic system according to atleast one example embodiment. The electronic system shown in FIG. 12 mayencompass the user verification apparatus 110 shown in FIG. 1. Referringto FIG. 12, the electronic system includes a sensor 1220, a processor1210, and a memory 1230. The sensor 1220, the processor 1210, and thememory 1230 may communicate with one another through a bus 1240. Thesensor 1210 may include, for example, a fingerprint sensor, an imagesensor, and an ECG sensor to detect biometric information of a userincluding, for example, a face, a fingerprint, an iris, a vein, palmlines, a shape of an ear, and an ECG. The sensor 1220 may detect thebiometric information of the user using a well-known method, forexample, a method of converting an optical image to an electricalsignal. The biometric information may be output to the processor 1210.

The processor 1210 may include at least one apparatus described withreference to FIGS. 1 through 11, or at least one method described withreference to FIGS. 1 through 11. For example, the processor 1210 mayinclude at least one of the controller 210, the biometric verifiers 220and 230, and the fusion model 240 illustrated in FIG. 2. The memory 1230may store a registered fingerprint image or registered images obtainedby the sensor 1220, an input fingerprint image or input images obtainedby the sensor 1220, matching results processed by the processor 1210,and/or matching scores calculated by the processor 1210. The memory 1230may be a volatile memory or a nonvolatile memory.

The processor 1210 may execute a program and control the electronicsystem. A program code to be executed by the processor 1210 may bestored in the memory 1230. The electronic system may be connected to anexternal device, for example, a personal computer (PC) or a network,through an input and output device (not shown), and exchange data withthe external device. The electronic system may include variouselectronic systems, for example, a mobile device such as a mobile phone,a smartphone, a personal digital assistant (PDA), a tablet computer, anda laptop computer, a computing device such as a PC, a tablet computer,and a netbook, and an electronic product such as a television (TV), asmart TV, and a security device for gate control.

In at least one example embodiment, the processor 1210 and memory 1230alone may implement the verification process shown in FIG. 11 andillustrated in the other figures, provided that input information isreceived from an external biometric sensor device.

The units and/or modules described herein may be implemented usinghardware components and software components. For example, the hardwarecomponents may include microphones, amplifiers, band-pass filters, audioto digital convertors, and processing devices. A processing device maybe implemented using one or more hardware device configured to carry outand/or execute program code by performing arithmetical, logical, andinput/output operations. The processing device(s) may include aprocessor, a controller and an arithmetic logic unit, a digital signalprocessor, a microcomputer, a field programmable array, a programmablelogic unit, a microprocessor or any other device capable of respondingto and executing instructions in a defined manner. The processing devicemay run an operating system (OS) and one or more software applicationsthat run on the OS. The processing device also may access, store,manipulate, process, and create data in response to execution of thesoftware. For purpose of simplicity, the description of a processingdevice is used as singular; however, one skilled in the art willappreciated that a processing device may include multiple processingelements and multiple types of processing elements. For example, aprocessing device may include multiple processors or a processor and acontroller. In addition, different processing configurations arepossible, such a parallel processors.

The software may include a computer program, a piece of code, aninstruction, or some combination thereof, to independently orcollectively instruct and/or configure the processing device to operateas desired, thereby transforming the processing device into a specialpurpose processor. Software and data may be embodied permanently ortemporarily in any type of machine, component, physical or virtualequipment, computer storage medium or device, or in a propagated signalwave capable of providing instructions or data to or being interpretedby the processing device. The software also may be distributed overnetwork coupled computer systems so that the software is stored andexecuted in a distributed fashion. The software and data may be storedby one or more non-transitory computer readable recording mediums.

The methods according to the above-described example embodiments may berecorded in non-transitory computer-readable media including programinstructions to implement various operations of the above-describedexample embodiments. The media may also include, alone or in combinationwith the program instructions, data files, data structures, and thelike. The program instructions recorded on the media may be thosespecially designed and constructed for the purposes of exampleembodiments, or they may be of the kind well-known and available tothose having skill in the computer software arts. Examples ofnon-transitory computer-readable media include magnetic media such ashard disks, floppy disks, and magnetic tape; optical media such asCD-ROM discs, DVDs, and/or Blue-ray discs; magneto-optical media such asoptical discs; and hardware devices that are specially configured tostore and perform program instructions, such as read-only memory (ROM),random access memory (RAM), flash memory (e.g., USB flash drives, memorycards, memory sticks, etc.), and the like. Examples of programinstructions include both machine code, such as produced by a compiler,and files containing higher level code that may be executed by thecomputer using an interpreter. The above-described devices may beconfigured to act as one or more software modules in order to performthe operations of the above-described example embodiments, or viceversa.

A number of example embodiments have been described above. Nevertheless,it should be understood that various modifications may be made to theseexample embodiments. For example, suitable results may be achieved ifthe described techniques are performed in a different order and/or ifcomponents in a described system, architecture, device, or circuit arecombined in a different manner and/or replaced or supplemented by othercomponents or their equivalents. Accordingly, other implementations arewithin the scope of the following claims.

It should be understood that example embodiments described herein shouldbe considered in a descriptive sense only and not for purposes oflimitation. Descriptions of features or aspects within each device ormethod according to example embodiments should typically be consideredas available for other similar features or aspects in other devices ormethods according to example embodiments. While at least one exampleembodiment have been particularly shown and described, it will beunderstood by one of ordinary skill in the art that variations in formand detail may be made therein without departing from the spirit andscope of the claims.

What is claimed is:
 1. A user verification method comprising: setting atermination stage of each biometric verifier of a plurality of biometricverifiers, such that each biometric verifier of the plurality ofbiometric verifiers is associated with a separate termination stage of aparticular combination of termination stages, respectively; executingthe plurality of biometric verifiers, based on the particularcombination of termination stages associated with the plurality ofbiometric verifiers, to generate a plurality of outputs; fusing theplurality of outputs based on the particular combination of terminationstages associated with the plurality of biometric verifiers to generatea result; and verifying a user based on the result.
 2. The method ofclaim 1, wherein each biometric verifier is configured to be executed tooutput an individual verification result through a set of stages of thebiometric verifier, the set of stages including at least one stage. 3.The method of claim 2, wherein, the set termination stage of thebiometric verifier is a particular stage of the plurality of stages, andeach biometric verifier is configured to be executed to output anindividual verification result corresponding to the set terminationstage of the biometric verifier.
 4. The method of claim 1, wherein thesetting includes setting a termination stage at least one biometricverifier based on a particular criterion.
 5. The method of claim 4,wherein the particular criterion includes an application type associatedwith a received verification request, a security level associated withthe received verification request, a sensing environment associated withthe user verification apparatus, a determination of whether the at leastone biometric verifier is to be executed to perform main verification orauxiliary verification, and/or a selection by a user at a userinterface.
 6. The method of claim 4, wherein the setting includessetting, to be the termination stage of the at least one biometricverifier, a particular stage of the plurality of stages of the at leastone biometric verifier at which a verification rate (VR) and a falseacceptance rate (FAR) associated with an individual verification resultof the particular stage at least meet a threshold VR and a thresholdFAR, respectively, based on the particular criterion.
 7. The method ofclaim 1, wherein the biometric verifiers are configured to be executedto perform biometric verification of different modalities.
 8. The methodof claim 1, wherein each biometric verifier of the plurality ofbiometric verifiers is configured to be executed to perform biometricverification based on received biometric information, the receivedbiometric information including one of a face, a fingerprint, an iris, avein, palm lines, a shape of an ear, and an electrocardiogram (ECG). 9.The method of claim 1, wherein the fusing includes fusing the pluralityof outputs based on executing a fusion model corresponding to theparticular combination of termination stages associated with theplurality of biometric verifiers among a plurality of fusion modelsassociated with separate, respective combinations of termination stagesassociated with the plurality of biometric verifiers.
 10. The method ofclaim 1, wherein the verifying includes verifying the user based oncomparing the result of the fusing and a threshold value correspondingto the plurality of termination stages of the plurality of biometricverifiers.
 11. The method of claim 1, wherein, at least one biometricverifier of the plurality of biometric verifiers includes a fingerprintverifier, the fingerprint verifier is configured to be executed tooutput an individual verification result based on executing each stageof a plurality of stages of the fingerprint verifier, executing a firststage of the plurality of stages includes outputting an overlapping areaand a matching score between a registered fingerprint image and an inputfingerprint image, and executing a second stage of the plurality ofstages includes outputting matching scores between the registeredfingerprint image and blocks generated based on partitioning the inputfingerprint image.
 12. The method of claim 1, wherein, at least onebiometric verifier of the plurality of biometric verifiers includes aface verifier, the face verifier is configured to be executed to outputan individual verification result of each layer based on comparingfeatures to be output by multiple layers in a neural network, based onan input image and features of a stored registered image correspondingto the layers.
 13. The method of claim 1, wherein the setting includesselecting one biometric verifier of the plurality of biometric verifiersas a main verifier, selecting another biometric verifier of theplurality of biometric verifiers as a sub-verifier, and selecting, froma plurality of separate combinations of a termination stage of the mainverifier and a termination stage of the sub-verifier, a particularcombination of the termination stage of the main verifier and thetermination stage of the sub-verifier that increases a level of thetermination stage of the main verifier.
 14. The method of claim 1,wherein the fusing includes fusing the plurality of outputs using afusion model configured to output a final verification result to verifythe user based on an input vector of a dimension corresponding to anoutput of the set termination stage.
 15. A non-transitorycomputer-readable medium storing instructions that, when executed by aprocessor, cause the processor to perform the method of claim
 1. 16. Auser verification apparatus comprising: a memory storing a program ofinstructions; and a processor configured to execute the program ofinstructions to set a termination stage of each biometric verifier of aplurality of biometric verifiers, such that each biometric verifier ofthe plurality of biometric verifiers is associated with a separatetermination stage of a particular combination of termination stages,respectively, execute the plurality of biometric verifiers, based on theparticular combination of termination stages associated with theplurality of biometric verifiers, to generate a plurality of outputs,and execute a fusion model to fuse the plurality of outputs based on theparticular combination of termination stages associated with theplurality of biometric verifiers to generate a verification result. 17.The apparatus of claim 16, wherein the processor is configured toexecute each biometric verifier to output an individual verificationresult through a plurality of stages of the biometric verifier.
 18. Theapparatus of claim 17, wherein, each set termination stage is aparticular stage of a plurality of stages associated with a particularbiometric verifier of the plurality of biometric verifiers, and theprocessor is configured to execute each biometric verifier to output anindividual verification result corresponding to the set terminationstage associated with the biometric verifier, of the plurality of stagesassociated with the biometric verifier.
 19. The apparatus of claim 16,wherein the processor is configured to set the termination stage of atleast one biometric verifier based on a particular criterion.
 20. Theapparatus of claim 19, wherein the particular criterion includes anapplication type associated with a received verification request, asecurity level associated with the received verification request, asensing environment associated with the user verification apparatus, adetermination of whether the at least one biometric verifier is to beexecuted to perform main verification or auxiliary verification, and/ora selection by a user at a user interface.
 21. The apparatus of claim19, wherein the processor is configured to set, to be the terminationstage of the at least one biometric verifier, a particular stage of theplurality of stages of the at least one biometric identifier at which averification rate (VR) and a false acceptance rate (FAR) associated withan individual verification result of the stage at least meet a thresholdVR and a threshold FAR, respectively, based on the particular criterion.22. The apparatus of claim 16, wherein the processor is configured toexecute separate biometric verifiers to perform biometric verificationof different modalities.
 23. The apparatus of claim 16, wherein theprocessor is configured to execute each biometric verifier of theplurality of biometric verifiers to perform biometric verification basedon received biometric information, the received biometric informationincluding one of a face, a fingerprint, an iris, a vein, palm lines, ashape of an ear, and an electrocardiogram (ECG).
 24. The apparatus ofclaim 16, wherein the processor is configured to fuse the plurality ofoutputs of the plurality of biometric verifiers, respectively, using afusion model corresponding to the particular combination of terminationstages associated with the plurality of biometric verifiers, among aplurality of fusion models associated with separate, respectivecombinations of termination stages associated with the plurality ofbiometric verifiers.
 25. The apparatus of claim 16, wherein, at leastone biometric verifier of the plurality of biometric verifiers includesa fingerprint verifier, the processor is configured to execute thefingerprint verifier to output an individual verification result basedon executing each stage of a plurality of stages of the fingerprintverifier, executing a first stage of the plurality of stages includesoutputting an overlapping area and a matching score between a registeredfingerprint image and an input fingerprint image, and executing a secondstage of the plurality of stages includes outputting matching scoresbetween the registered fingerprint image and blocks generated based onpartitioning the input fingerprint image.
 26. The apparatus of claim 16,wherein, at least one biometric verifier of the plurality of biometricverifiers includes a face verifier, the processor is configured toexecute the face verifier to output an individual verification result ofeach layer based on comparing features to be output by multiple layersin a neural network, based on an input image and features of a storedregistered image corresponding to the layers.
 27. The apparatus of claim16, wherein executing the fusion model includes outputting a finalverification result for user verification based on an input vector of adimension corresponding to an output of the particular combination oftermination stages associated with the plurality of biometric verifiers.28. The apparatus of claim 16, wherein the processor is configured toselect one biometric verifier of the plurality of biometric verifiers asa main verifier, select another biometric verifier of the plurality ofbiometric verifiers as a sub-verifier, set a minimum stage of the mainverifier, from among a plurality of stages of the main verifier, to be atermination stage of the main verifier, and set a maximum stage of thesub-verifier, from among a plurality of stages of the sub-verifier, tobe a termination stage of the sub-verifier.
 29. A user verificationapparatus, comprising: a memory storing a program of instructions; and aprocessor configured to execute the program of instructions to receive auser verification request, the user verification request including acriterion, set a termination stage of a biometric verifier based on thecriterion, execute the biometric verifier, based on the set terminationstage, to generate an individual verification result, and verify a userbased on the individual verification result.
 30. The user verificationapparatus of claim 29, wherein the criterion includes an applicationtype associated with the received verification request, a security levelassociated with the received verification request, a sensing environmentassociated with the user verification apparatus, a determination ofwhether the biometric verifier is to be executed to perform mainverification or auxiliary verification, and/or a selection by a user ata user interface.
 31. The user verification apparatus of claim 29,wherein the setting includes setting, to be the termination stage of thebiometric verifier, a particular stage of a plurality of stages of thebiometric verifier at which a verification rate (VR) and a falseacceptance rate (FAR) associated with an individual verification resultof the particular stage at least meet a threshold VR and a thresholdFAR, respectively, based on the criterion.
 32. The user verificationapparatus of claim 29, wherein, the processor further configured toexecute the program of instructions to generate an unlocking commandsignal to enable at least partial user access to a device, based on theverifying.
 33. The user verification apparatus of claim 32, wherein, theuser verification apparatus includes a vehicle configured to transportone or more occupants, and the generating the unlocking command signalincludes, selectively granting, to the user, access to an interior ofthe vehicle based on the verifying, and/or selectively grant, to theuser, control over one or more driving elements of the vehicle based onthe verifying.